Leveraging AI in Contract Management for Efficiency and Accuracy

Importance and Benefits

According to a study, errors in drawing up contracts can lead to significant issues. Aside from creating confusion and ambiguity between parties, these mistakes can result in legal disputes and potential financial losses. It may even render the agreement unenforceable. Utilizing AI to manage contracts eradicates those issues and helps companies gain the following:

• Increased efficiency and accuracy – With automated contract reviews and real-time monitoring, managers can pinpoint inconsistencies, errors, and potential breaches faster than manual inspections.
• Lesser administrative burden – Traditional contract processes are time-intensive. AI automates repetitive tasks, enabling relevant personnel (e.g., corporate counsel, procurement managers, compliance officers, etc.) to focus on the nitty-gritty of the operations.
• Better decision-making – New tech can go through historical data and future trends, helping organizations make better decisions about supplier selection, contract terms, and negotiations.
• Reduced operational costs – Aside from saving money by streamlining routine tasks, AI aids in identifying and resolving potential risks early on. This significantly reduces costs, particularly those associated with incidents, contract disputes, and litigation.
• Stronger compliance with regulations – Besides automating scheduling tasks and compliance checks, contract management platforms can monitor regulatory changes, operational activities, and performance levels and alert organizations to potential risks.

Practical Applications

More and more companies are experiencing the benefits of AI-powered tools for managing documents. For those still wondering how this is possible, here are specific tasks in the contract management life cycle that artificial intelligence streamlines:

Contract Drafting

Law firms, financial institutions, and large enterprises utilize NLP and ML to create standardized templates and custom clauses based on a database of legal language and past agreements.

Contract Review

Legal and tech firms leverage Robotic Process Automation (RPA) with ML and NLP to speed up the review process, assess risks, flag compliance issues, and suggest modifications.

Obligation Tracking

Predictive analytics tracks and monitors contract obligations, alerting teams to upcoming deadlines, renewals, and compliance checkpoints. Large multinational corporations with extensive vendor agreements take advantage of this tech to handle multi-tiered obligations.

Data Extraction

Optical Character Recognition (OCR), semantic search, and NLP extract key terms, clauses, and dates from documents, automatically categorizing them for easy access and retrieval. Software solution providers and large retail stores utilize this to minimize data entry errors and speed up data organization.

Contract Analysis and Benchmarking

Competitive industries like tech, finance, and manufacturing employ a combination of NLP, ML, and advanced data analytics to evaluate contract terms, verifying they meet industry best practices.

How to Integrate AI in Contract Management

Numerous research has shown how AI cuts the review time by nearly 80%, speeding up decision-making and risk management. However, success isn’t guaranteed if the tech isn’t well-integrated into the system. Here’s a foolproof approach that can help with the implementation:

Step 1: Assess the current process.

Understanding existing practices provides a baseline that helps identify pain points, inefficiencies, and areas where artificial intelligence can add value. Relevant personnel can start by conducting an audit of the process, tracking the following key metrics:

• Drafting period
• Review period
• Error rates
• Compliance risks
• Costs involved in manual workflows

Step 2: Define the objectives.

The integration should be consistent with the organization’s overall goals for contract management. By setting measurable goals, such as reducing contract cycle time by 30% or increasing contract accuracy, the company can better allocate funds, time, and personnel.

Step 3: Choose the right tools.

Selecting the right AI tech is vital. Aside from reviewing its capabilities, managers should also ascertain its compatibility with the company’s existing systems. Choosing the wrong one can make processes even more complex, causing employee resistance, data privacy risks, and expensive maintenance costs.

These are the most common AI tech for managing contracts:

• NLP can be used to analyze complex legal jargon, especially when understanding key clauses, obligations, and risks.
• OCR digitizes physical contracts, making them easier to search and analyze.
• Robotic Process Automation (RPA) automates repetitive tasks such as data entry, document routing, and contract renewals.

Step 4: Train the team.

For successful AI adoption, employees directly involved in contract management should understand these tools and how they’re used. These are the most effective ways to teach the technology to workers:

• Hands-on workshops utilizing real-world scenarios for practical AI applications
• Role-playing exercises with interactive simulations for team collaboration and scenario-based learning
• Case study analysis for critical thinking and problem-solving

One of the most common concerns workers have is that AI will replace them. These worries can be alleviated through training, highlighting the fact that automation will only assist and not fully replace their expertise.

Step 5: Monitor the performance of AI tools.

Tracking the AI’s performance and its impact on workflow efficiency helps ensure that established goals are being met. It also identifies areas for improvement. These are the metrics to check:

• Time to contract or the total duration from contract initiation to final execution
• Contract creation and review time or the time spent creating and reviewing agreements.
• Contract error rate to measure the mistakes identified and corrected by the AI tool
• Contract consistency rate to evaluate the language and terms across different contracts
• Compliance rate to check the adherence to regulatory and legal requirements
• Cost savings and ROI to calculate the reduction in administrative costs and how much the company gains from the AI tool
• Reduced manual effort or the decrease in manual work hours
• User adoption rate or the number of users actively using the AI tool

Step 6: Iterate and improve.

Regular improvements maximize the long-term value of the technology. The process, AI tools used, and user training should be continuously updated and improved based on evolving needs and stakeholder feedback.